
"""simple docstring"""






from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403





def __A    ( a_			:				int		,		a_			:				Any		,		a_			:				int = "x"		,		a_			:				Optional[Any] = 10**-10		,		a_			:				int = 1		,		)->				Dict:




		'''simple docstring'''






		SCREAMING_SNAKE_CASE							:  Any					=			symbols(a__  )
		SCREAMING_SNAKE_CASE							:  Optional[Any]					=			lambdify(a__		,		a__  )
		SCREAMING_SNAKE_CASE							:  int					=			lambdify(a__		,		diff(a__		,		a__  )  )

		SCREAMING_SNAKE_CASE							:  Tuple					=			starting_point

		while True:
				if diff_function(a__  ) != 0:
						SCREAMING_SNAKE_CASE							:  int					=			prev_guess - multiplicity * func(a__  ) / diff_function(
						    a__  )
				else:
						raise ZeroDivisionError('''Could not find root'''  ) from None

				# Precision is checked by comparing the difference of consecutive guesses
				if abs(next_guess - prev_guess  ) < precision:
						return next_guess

				SCREAMING_SNAKE_CASE							:  Tuple					=			next_guess


# Let's Execute
if __name__ == "__main__":
					# Find root of trigonometric function
					# Find value of pi
					print(f'''The root of sin(x) = 0 is {newton_raphson("sin(x)", 2)}''')

					# Find root of polynomial
					# Find fourth Root of 5
					print(f'''The root of x**4 - 5 = 0 is {newton_raphson("x**4 -5", 0.4 +5J)}''')

					# Find value of e
					print(
					    "The root of log(y) - 1 = 0 is ",
					    f'''{newton_raphson("log(y) - 1", 2, variable="y")}''',
					)

					# Exponential Roots
					print(
					    "The root of exp(x) - 1 = 0 is",
					    f'''{newton_raphson("exp(x) - 1", 10, precision=0.0_0_5)}''',
					)

					# Find root of cos(x)
					print(f'''The root of cos(x) = 0 is {newton_raphson("cos(x)", 0)}''')








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__snake_case				:      int   		=			{
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:      int   		=			["""LlamaTokenizer"""]

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:      int   		=			["""LlamaTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:      Union[str, Any]   		=			[
	    """LlamaForCausalLM""",
	    """LlamaModel""",
	    """LlamaPreTrainedModel""",
	    """LlamaForSequenceClassification""",
	]


if TYPE_CHECKING:
	from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama import LlamaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama_fast import LlamaTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
	import sys

	__snake_case				:      Dict   		=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


